Personality Profiling For Career Recommendation In Computing

Author : Nethisha Weerakoon

Abstract :The article focuses on how matching individual characteristics with needs has become a pertinent issue in the time of sweeping technological change, growing demand for specialized education and career options taken in one breath. This work presents the design of an integrated system, uniting learning type identification, adaptive learning paths, and personality prediction for web development professionals, including career recommendation and recruitment guidance. Among the major features of the system are addressing personalized job advice and job matching, adaptation of learning path development, tracking user mood, and recruitment guidance. The methodology used in this approach combines modern machine learning techniques with survey data and psychometric tests to identify relationships between personality traits, learning styles, and professional outcome measures. This adaptive system will support users by recommending optimal career paths, individualizing training materials, and aiding companies in recruiting web-development professionals. One anticipates a comprehensive platform which will facilitate hiring and management of talents, besides personalized learning and career development. This research promotes better decision-making by bridging the gaps between personality profiling, adaptive education, and career recommendation systems in matching skills to opportunities in the web development industry.

Keywords :Personality Prediction, Adaptive Learning Pathways, Job Matching, Emotion Analysis, Recruitment Guidance

Conference Name :International Conference on Artificial Intelligence in Information and Communication (ICAIIC-25)

Conference Place Colombo, Sri Lanka

Conference Date 22nd Mar 2025